Revise implementation of ht_neuron

extras/ConnPlotter/tcd_nest.py

@@ -32,7 +32,9 @@
 SynapsesNEST. The constructor will import NEST to obtain all necessary
 information. TCD can then be obtained by calling the generated object.
 
-NB: At present, TCD is supported only for the ht_model.
+NB: At present, TCD is supported only for the ht_model. NMDA charge
+    deposition is based on steady-state value for open channels at given
+    voltage.
 """
 
 # ----------------------------------------------------------------------------
@@ -129,8 +131,8 @@ def __init__(self, syn, props):
             syn is name of synapse type.
             props is property dictionary of ht_neuron.
             """
-            td = props[syn + '_Tau_2']  # decay time
-            tr = props[syn + '_Tau_1']  # rise time
+            td = props[syn + '_tau_2']  # decay time
+            tr = props[syn + '_tau_1']  # rise time
             # integral over g(t)
             self._int_g = (props[syn + '_g_peak'] * (td - tr) /
                            ((tr / td) ** (tr / (td - tr)) -
@@ -141,7 +143,7 @@ def __call__(self, V):
             """
             V is membrane potential.
             """
-            return - self._int_g * (V - self._e_rev)
+            return -self._int_g * (V - self._e_rev)
 
         def __str__(self):
             return "_int_g = %f, _e_rev = %f" % (self._int_g, self._e_rev)
@@ -151,21 +153,24 @@ def __str__(self):
     class _TcdNMDA(object):
         """
         Class representing NMDA synapse model in ht_neuron.
+
+        Note: NMDA charge deposition is based on steady-state value
+              for open channels at given voltage.
         """
 
         def __init__(self, props):
             """
             props is property dictionary of ht_neuron.
             """
-            td = props['NMDA_Tau_2']  # decay time
-            tr = props['NMDA_Tau_1']  # rise time
+            td = props['tau_decay_NMDA']  # decay time
+            tr = props['tau_rise_NMDA']  # rise time
             # integral over g(t)
-            self._int_g = (props['NMDA_g_peak'] * (td - tr) /
+            self._int_g = (props['g_peak_NMDA'] * (td - tr) /
                            ((tr / td) ** (tr / (td - tr)) -
                             (tr / td) ** (td / (td - tr))))
-            self._e_rev = props['NMDA_E_rev']
-            self._v_act = props['NMDA_Vact']
-            self._s_act = props['NMDA_Sact']
+            self._e_rev = props['E_rev_NMDA']
+            self._v_act = props['V_act_NMDA']
+            self._s_act = props['S_act_NMDA']
 
         def __call__(self, V):
             """

models/ht_connection.h

@@ -31,24 +31,23 @@
 
   Description:
   This synapse implements the depression model described in [1, p 1678].
+  See docs/model_details/HillTononi.ipynb for details.
+
   Synaptic dynamics are given by
 
-  P'(t) = ( 1 - P ) / tau_p
+  P'(t) = ( 1 - P ) / tau_P
   P(T+) = (1 - delta_P) P(T-)   for T : time of a spike
   P(t=0) = 1
 
   w(t) = w_max * P(t)  is the resulting synaptic weight
 
   Parameters:
      The following parameters can be set in the status dictionary:
-     tauP     double - synaptic vesicle pool recovery time constant [ms]
+     tau_P    double - synaptic vesicle pool recovery time constant [ms]
      delta_P  double - fractional change in vesicle pool on incoming spikes
                        [unitless]
      P        double - current size of the vesicle pool [unitless, 0 <= P <= 1]
 
-  Warning:
-  THIS SYNAPSE MODEL HAS NOT BEEN TESTED EXTENSIVELY!
-
   References:
    [1] S Hill and G Tononi (2005). J Neurophysiol 93:1671-1698.
 
@@ -61,7 +60,7 @@
 
 /**
  * Class representing a synapse with Hill short term plasticity.  A
- * suitale Connector containing these connections can be obtained from
+ * suitable Connector containing these connections can be obtained from
  * the template GenericConnector.
  */
 
@@ -178,15 +177,12 @@ HTConnection< targetidentifierT >::send( Event& e,
   double t_lastspike,
   const CommonSynapseProperties& )
 {
-  double h = e.get_stamp().get_ms() - t_lastspike;
-  Node* target = get_target( t );
-  // t_lastspike_ = 0 initially
-
   // propagation t_lastspike -> t_spike, t_lastspike_ = 0 initially, p_ = 1
+  const double h = e.get_stamp().get_ms() - t_lastspike;
   p_ = 1 - ( 1 - p_ ) * std::exp( -h / tau_P_ );
 
   // send the spike to the target
-  e.set_receiver( *target );
+  e.set_receiver( *get_target( t ) );
   e.set_weight( weight_ * p_ );
   e.set_delay( get_delay_steps() );
   e.set_rport( get_rport() );
@@ -200,8 +196,8 @@ template < typename targetidentifierT >
 HTConnection< targetidentifierT >::HTConnection()
   : ConnectionBase()
   , weight_( 1.0 )
-  , tau_P_( 50.0 )
-  , delta_P_( 0.2 )
+  , tau_P_( 500.0 )
+  , delta_P_( 0.125 )
   , p_( 1.0 )
 {
 }
@@ -222,9 +218,9 @@ HTConnection< targetidentifierT >::get_status( DictionaryDatum& d ) const
 {
   ConnectionBase::get_status( d );
   def< double >( d, names::weight, weight_ );
-  def< double >( d, "tau_P", tau_P_ );
-  def< double >( d, "delta_P", delta_P_ );
-  def< double >( d, "P", p_ );
+  def< double >( d, names::tau_P, tau_P_ );
+  def< double >( d, names::delta_P, delta_P_ );
+  def< double >( d, names::P, p_ );
   def< long >( d, names::size_of, sizeof( *this ) );
 }
 
@@ -236,12 +232,12 @@ HTConnection< targetidentifierT >::set_status( const DictionaryDatum& d,
   ConnectionBase::set_status( d, cm );
 
   updateValue< double >( d, names::weight, weight_ );
-  updateValue< double >( d, "tau_P", tau_P_ );
-  updateValue< double >( d, "delta_P", delta_P_ );
-  updateValue< double >( d, "P", p_ );
+  updateValue< double >( d, names::tau_P, tau_P_ );
+  updateValue< double >( d, names::delta_P, delta_P_ );
+  updateValue< double >( d, names::P, p_ );
 
   if ( tau_P_ <= 0.0 )
-    throw BadProperty( "tau_P >= 0 required." );
+    throw BadProperty( "tau_P > 0 required." );
 
   if ( delta_P_ < 0.0 || delta_P_ > 1.0 )
     throw BadProperty( "0 <= delta_P <= 1 required." );